The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell‐released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV‐associated functional activities. Finally, a checklist is provided with summaries of key points.

BACKGROUND: Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels. Quantification of miRNA transcripts implicates data normalization using endogenous and exogenous reference genes for data correction. However, there is no consensus about an optimal normalization strategy. The choice of a reference gene remains problematic and can have a serious impact on the actual available transcript levels and, consequently, on the biological interpretation of data. CONTENT: In this review article we discuss the reliability of the use of small RNAs, commonly reported in the literature as miRNA expression normalizers, and compare different strategies used for data normalization. SUMMARY: A workflow strategy is proposed for normalization of miRNA expression data in an attempt to provide a basis for the establishment of a global standard procedure that will allow comparison across studies.

Extracellular Vesicles (EVs) have been intensively explored for therapeutic delivery of proteins. However, methods to quantify cargo proteins loaded into engineered EVs are lacking. Here, we describe a workflow for EV analysis at the single‐vesicle and single‐molecule level to accurately quantify the efficiency of different EV‐sorting proteins in promoting cargo loading into EVs. Expi293F cells were engineered to express EV‐sorting proteins fused to green fluorescent protein (GFP). High levels of GFP loading into secreted EVs was confirmed by Western blotting for specific EV‐sorting domains, but quantitative single‐vesicle analysis by Nanoflow cytometry detected GFP in less than half of the particles analysed, reflecting EV heterogeneity. Anti‐tetraspanin EV immunostaining in ExoView confirmed a heterogeneous GFP distribution in distinct subpopulations of CD63⁺, CD81⁺, or CD9⁺ EVs. Loading of GFP into individual vesicles was quantified by Single‐Molecule Localization Microscopy. The combined results demonstrated TSPAN14, CD63 and CD63/CD81 fused to the PDGFRβ transmembrane domain as the most efficient EV‐sorting proteins, accumulating on average 50–170 single GFP molecules per vesicle. In conclusion, we validated a set of complementary techniques suitable for high‐resolution analysis of EV preparations that reliably capture their heterogeneity, and propose highly efficient EV‐sorting proteins to be used in EV engineering applications.

Cancer cells actively promote their tumorigenic behavior by reprogramming gene expression. Loading intraluminal vesicles with specific miRNAs and releasing them into the tumor microenvironment as exosomes is one mechanism of reprogramming whose regulation remains to be elucidated. Here, we report that miR-6126 is ubiquitously released in high abundance from both chemosensitive and chemoresistant ovarian cancer cells via exosomes. Overexpression of miR-6126 was confirmed in healthy ovarian tissue compared with ovarian cancer patient samples and correlated with better overall survival in patients with high-grade serous ovarian cancer. miR-6126 acted as a tumor suppressor by directly targeting integrin-β1, a key regulator of cancer cell metastasis. miR-6126 mimic treatment of cancer cells resulted in increased miR-6126 and decreased integrin-β1 mRNA levels in the exosome. Functional analysis showed that treatment of endothelial cells with miR-6126 mimic significantly reduced tube formation as well as invasion and migration capacities of ovarian cancer cells in vitro. Administration of miR-6126 mimic in an orthotopic mouse model of ovarian cancer elicited a relative reduction in tumor growth, proliferating cells, and microvessel density. miR-6126 inhibition promoted oncogenic behavior by leading ovarian cancer cells to release more exosomes. Our findings provide new insights into the role of exosomal miRNA-mediated tumor progression and suggest a new therapeutic approach to disrupt oncogenic phenotypes in tumors. Cancer Res; 76(24); 7194–207. ©2016 AACR.

Non-coding RNAs have long been associated with cancer development and progression, and since their earliest discovery, their clinical potential in identifying and characterizing the disease has been pursued. Long non-coding (lncRNAs), a diverse class of RNA transcripts >200 nucleotides in length with limited protein coding potential, has been only modestly studied relative to other categories of non-coding RNAs. However, recent data suggests they too may be important players in cancer. In this article, we consider the value of lncRNAs in the clinical setting, and in particular their potential roles as diagnostic and prognostic markers in cancer. Furthermore, we summarize the most significant studies linking lncRNA expression in human biological samples to cancer outcomes. The diagnostic sensitivity, specificity and validity of these non-coding RNA transcripts is compared in the various biological compartments in which they have been detected including tumor tissue, whole body fluids and exosomes.